Method for evaluating blush in myocardial tissue

ABSTRACT

Vessel perfusion and myocardial blush are determined by analyzing fluorescence signals obtained in a static region-of-interest (ROI) in a collection of fluorescence images of myocardial tissue. The blush value is determined from the total intensity of the intensity values of image elements located within the smallest contiguous range of image intensity values containing a predefined fraction of a total measured image intensity of all image elements within the ROI. Vessel (arterial) peak intensity is determined from image elements located within the ROI that have the smallest contiguous range of highest measured image intensity values and contain a predefined fraction of a total measured image intensity of all image elements within the ROI. Cardiac function can be established by comparing the time differential between the time of peak intensity in a blood vessel and that in a region of neighboring myocardial tissue both pre and post procedure.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of U.S. application Ser. No.13/850,063, pending, filed Mar. 25, 2013, which is a divisional of U.S.application Ser. No. 12/841,659, now U.S. Pat. No. 8,406,860, which is acontinuation-in-part of PCT International Application No.PCT/CA2009/00073, filed Jan. 23, 2009, which claims the benefit of U.S.Provisional Application No. 61/023,818, filed Jan. 25, 2008, the entirecontents of which are incorporated herein by reference. This applicationalso claims the benefit of prior filed U.S. Provisional Application No.61/243,688, filed Sep. 18, 2009, the entire contents of which areincorporated herein by reference.

BACKGROUND OF THE INVENTION

The invention relates to a method for evaluating myocardial blush intissue from images recorded following injection of fluorescent dyes.

TIMI (Thrombolysis In Myocardial Infarction) studies initially suggestedthat successful restoration of flow in an infarcted artery was the majorgoal of reperfusion. However, substantial evidence has grown over theyears showing that distortion of microvasculature and myocardialperfusion is often present despite epicardial artery patency. This mightbe the result of a combination of distal embolization and reperfusioninjury with cellular and extracellular edema, neutrophil accumulationand release of detrimental oxygen free radicals.

Myocardial blush was first defined by van't Hof et al. as a qualitativevisual assessment of the amount of contrast medium filling a regionsupplied by an epicardial coronary artery. It is graded as MyocardialBlush Grade: 0 (=no myocardial blush or contrast density), 1 (=minimalmyocardial blush or contrast density), 2 (=myocardial blush or contrastdensity which exists to lesser extent and its clearance is diminishedcompared to non-infarct-related coronary artery), and 3 (=normalmyocardial blush or contrast density comparable with that obtainedduring angiography of a contralateral or ipsilateral non-infarct-relatedcoronary artery). When myocardial blush persists (long “wash-out rate”or “staining”), it suggests leakage of the contrast medium into theextravascular space or impaired venous clearance and is graded 0.

The consequences of microvascular damage are extremely serious. Inpatients treated with thrombolytics for acute myocardial infarction,impaired myocardial perfusion as measured by the myocardial blush scorecorresponds to a higher mortality, independent of epicardial flow.Myocardial blush grade correlates significantly with ST segmentresolution on ECGs, enzymatic infarct size, LVEF, and is an independentpredictor of long-term mortality. Myocardial blush grade may be the bestinvasive predictor of follow-up left ventricular function. Determiningthe myocardial blush has emerged as a valuable tool for assessingcoronary microvasculature and myocardial perfusion in patientsundergoing coronary angiography and angioplasty.

The degree of blush that appears during imaging (e.g., imaging with afluorescent dye, such as ICG) is directly related to the underlyingtissue perfusion. Conventionally, to quantitatively characterizekinetics of dye entering the myocardium using the angiogram, digitalsubtraction angiography (DSA) has been utilized to estimate the rate ofbrightness (gray/sec) and the rate of growth of blush (cm/sec). DSA isperformed at end diastole by aligning cine frame images before the dyefills the myocardium with those at the peak of a myocardial filling tosubtract spine, ribs, diaphragm, and epicardial artery. A representativeregion of myocardium is sampled that is free of overlap by epicardialarterial branches to determine the increase in the grayscale brightnessof the myocardium at peak intensity. The circumference of the myocardialblush is then measured using a handheld planimeter. The number of framesrequired for the myocardium to reach peak brightness is converted intotime by dividing the frame count by the frame rate. This approach isquite time-consuming and is difficult to perform on a beating heart andto conclude within a reasonable time.

Generally, conventional techniques gathering statistical informationabout a ROI rely on algorithms that track the ROI during movement of theunderlying anatomy and attempt to keep the ROI localized in the sametissue portion. For example, the user can draw an initial ROI in theimage, ignoring any blood vessels not to be included in the calculation,with the initial ROI then adjusted to the moving anatomy through lineartranslation, rotation, and distortion. However, this approach iscomputationally intensive and not reliable with low contrast images.

Accordingly, there is a need for a method to determine blush ofmyocardial tissue while the heart is beating, to eliminate effects fromfeatures other than myocardial tissue that may migrate into the regionof interest (blood vessels, clips, the surgeon's hands, etc. . . . ),and to produce useful information for the surgeon during a medicalprocedure within a “reasonable time,” if not within “real time.”

There is also a need for measuring improvement in cardiac function bymeasuring the time differential between when contrast in a blood vesselreaches its peak intensity and when the contrast in a neighboring regionin the myocardial tissue reaches its corresponding peak. If this timedifferential decreases after a medical procedure as compared to beforethe procedure, under uniform hemodynamic conditions cardiac function canbe said to have improved. A method for tracking blood vessels duringimage acquisition improves our ability to locate the time at which thecontrast in a blood vessel achieves its peak intensity.

SUMMARY OF THE INVENTION

The present invention is directed to a method for evaluating myocardialblush in tissue from images recorded following injection of fluorescentdyes using a static ROI (Region-of-Interest) that is fixed in positionon the image while the heart (or other tissue of interest) moves underit in the image sequence. The static ROI uses a statistical technique toeliminate intensity outliers and to evaluate only those pixels that haveless inter-pixel intensity variance. The technique is highly robust, andthe results depend only insignificantly on changes to the ROI size andposition, providing the ROI is placed in the same general region of theanatomy.

According to one aspect of the invention, a method for determiningperfusion in myocardial tissue using fluorescence imaging, includes thesteps of defining a static region of interest (ROI) in an image of themyocardial tissue, measuring fluorescence intensity values of imageelements (pixels) located within the ROI, and determining a blush valuefrom an average of the intensity values of image elements located withina smallest contiguous range of image intensity values containing a firstpredefined fraction of a total measured image intensity of all imageelements within the ROI.

Advantageous embodiments may include one or more of the followingfeatures. The smallest range of contiguous image intensity values may bedetermined from a histogram of a frequency of occurrence of the measuredimage intensity values, wherein the first predefined fraction may bebetween 70% and 30%, preferably between 60% and 40%, and most preferablyat about 50%. Blush values are determined, optionally continuously, overa predefined period of time. At least one of the blush rate and thewashout rate may be determined from the slope of the time-dependentblush values.

Alternatively or in addition, the blush and associated perfusion may bedetermined by defining a second static ROI in the image of themyocardial tissue, with the second ROI including an arterial bloodvessel, and determining a measure of the peak intensity of the arterialblood vessel from a total intensity of the intensity values of imageelements located within a smallest contiguous range of high imageintensity values containing a second predefined fraction, for example20%, of a total measured image intensity of brightest image elementswithin the ROI. This measurement can then be used to determine anoutcome of a procedure by comparing an elapsed time between a maximumblush value and maximum measure of perfusion before the procedure and anelapsed time between a maximum blush value and maximum measure ofperfusion after the procedure.

According to another aspect of the invention, a method for tracking ablood vessel in an image includes the steps of (a) acquiring afluorescence image of tissue containing a blood vessel, (b) delimiting asegment of the blood vessel with boundaries oriented substantiallyperpendicular to a longitudinal direction of the blood vessel, (c)constructing at least one curve extending between the delimitingboundaries and located within lateral vessel walls of the blood vessel,wherein the at least one curve terminates at the delimiting boundariessubstantially perpendicular to the boundaries, and (d) determining afluorescence signal intensity in the fluorescence image along the atleast one curve, with the signal intensity being representative ofvessel perfusion.

In one exemplary embodiment, the at least one curve may be defined by aspline function. For example, more than one curve may be constructed andthe fluorescence signal intensity may be determined by averaging thesignal intensity from points on the curves having a substantiallyidentical distance from one of the delimiting boundaries.

Advantageously, the position of the lateral vessel walls in thefluorescence image may be determined using an edge-detection algorithm,such as a Laplacian-of-a-Gaussian operator.

In another exemplary embodiment, time-sequential fluorescence images ofthe tissue containing the blood vessel may be acquired. Characteristicdimensions of the delimited segment may then be determined from thelocation of the lateral vessel walls in the first image, and positionsof lateral vessel walls may be determined in at least one second image.The characteristic dimensions from the first image may then be matchedto the positions of lateral vessel walls in the second image to find alocation of the lateral vessel walls of the first image in the at leastone second image. The steps (c) and (d) above are then repeated for thesecond image or images.

Advantageously, an average fluorescence signal intensity of all pointsmay be computed along the curve and a change in perfusion of the bloodvessel may be determined from a change in the average fluorescencesignal intensity between the time-sequential images.

These and other features and advantages of the present invention willbecome more readily appreciated from the detailed description of theinvention that follows and from the appended drawings.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 shows schematically a camera system for observing ICGfluorescence;

FIG. 2 shows an ICG fluorescent cardiac image, with the rectangledelineating a static ROI on the imaged area;

FIG. 3 shows a histogram of the number of pixels (vertical axis) as afunction of the measured brightness value (horizontal axis);

FIG. 4 shows the location of pixels within the static ROI that containat least 50% of the intensity counts over the smallest set of adjacenthistogram bins in FIG. 3;

FIG. 5 shows the static ROI of FIG. 2 (top image) and a smaller staticROI (bottom image) located within the ROI of the top image;

FIG. 6 shows the time dependence of the computed average intensity forthe pixels highlighted in FIG. 4 (top image) and for the smaller staticROI of FIG. 5 (bottom image) taken over a 28 second time period;

FIG. 7 shows an ICG fluorescent cardiac image with a static ROI before asurgical procedure (top image), and after the procedure (bottom image);

FIG. 8 shows the time evolution of the average blush intensity for thepixels within the ROI of FIG. 7 before the procedure (top image) andafter the procedure (bottom image) taken over a 28 second time period;

FIG. 9 shows delineation of a segment of a blood vessel for analysiswith the method of the invention;

FIG. 10 shows the delineated segment of FIG. 9 with lines terminating atthe vessel walls and line normals at the longitudinal end points;

FIG. 11 shows the vessel walls and line normals at the longitudinal endpoints of FIG. 10 with proper orientation;

FIG. 12 shows splines connecting the longitudinal end points of FIG. 11and a longitudinal intensity profile (upper left corner) taken before aprocedure;

FIG. 13 shows splines connecting the longitudinal end points togetherwith a longitudinal intensity profile (upper left corner) and the timedependence of the intensity profile (upper right corner) taken after aprocedure.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

FIG. 1 shows schematically a device for non-invasively determining blushof myocardial tissue by ICG fluorescence imaging. An infrared lightsource, for example, one or more diode lasers or LEDs, with a peakemission of about 780-800 nm for exciting fluorescence in ICG is locatedinside housing 1. The fluorescence signal is detected by a CCD camera 2having adequate near-IR sensitivity; such cameras are commerciallyavailable from several vendors (Hitachi, Hamamatsu, etc.). The CCDcamera 2 may have a viewfinder 8, but the image may also be viewedduring the operation on an external monitor which may be part of anelectronic image processing and evaluation system 11.

A light beam 3, which may be a divergent or a scanned beam, emerges fromthe housing 1 to illuminate an area of interest 4, i.e. the area wherethe blush of myocardial tissue is to be measured. The area of interestmay be about 10 cm×10 cm, but may vary based on surgical requirementsand the available illumination intensity and camera sensitivity.

A filter 6 is typically placed in front of the camera lens 7 to blockexcitation light from reaching the camera sensor, while allowingfluorescence light to pass through. The filter 6 may be an NIR long-wavepass filter (cut filter), which is only transparent to wavelengthsgreater than about 815 nm, or preferably a bandpass filter transmittingat peak wavelengths of between about 830 and about 845 nm and having afull width at half maximum (FWHM) transmission window of between about10 nm and 25 nm in order to block the excitation wavelength band. Thecamera 2 may also be designed to acquire a color image of the area ofinterest to allow real-time correlation between the fluorescence imageand the color image.

In general, the surgeon is interested in how well the blood is perfusingthe tissue in the area within a region of interest (ROI). Blood vesselsvisible in the image typically include major blood vessels, e.g.,arteries; however, arterial blood flow may not be of interest to thesurgeon when considering perfusion of the surrounding myocardial tissue.Because these blood vessels may have either a higher or a lowerbrightness in the image, depending on the phase of the cardiac cycle,contributions from blood vessels to the measured image brightness mayalter the myocardial blush grade by skewing the average image brightnessupward or downward. In order to obtain a correct value for themyocardial blush, the contributions from the blood vessels must beeliminated before the blush grade is computed.

FIG. 2 shows a typical ICG fluorescent image of a heart showing bloodvessels and myocardial tissue, with a rectangle delineating a static ROIon the imaged area. The ROI is static, meaning that it does not tracktissue movement when the heart is beating. This simplifies thecomputation, while the results computed with the method of the inventionare robust and largely insensitive to tissue movement.

To compute meaningful average blush intensity within the delineatedstatic ROI, the following needs to be taken into consideration:

-   -   1 The selected area of the anatomy within the ROI should consist        primarily of myocardial tissue, while minimizing the effects        from blood vessels, clips, etc. that appear in the ROI and may        move in and out of the ROI when the heart is beating.    -   2 The measured myocardial blush value should be substantially        independent of the size of the ROI in the selected area of the        anatomy.

According to one embodiment illustrated in FIG. 3, a histogram of thegrayscale intensity values in the ROI of FIG. 2 is generated. Thehorizontal axis of the histogram represents the full range of intensityvalues arranged in bins (e.g., 28=256 bins for an 8-bit imagerepresenting pixel intensities 0 to 255), whereas the vertical axisindicates the number of pixels for each intensity value in a bin. Incomparison, a histogram of a 12-bit image would have 212=4,096 intensitybins.

A sliding window W is applied across the abscissa, and the smallest setof adjacent histogram bins containing in excess of a predeterminedpercentage of the total intensity is determined. In the illustratedexample, a percentage value of 50% is selected as criterion for the binsto be included, although other values can be selected as long as theseselected values exclude outliers and provide a reliable assessment ofthe blush. For the histogram depicted in FIG. 3, the smallest set ofadjacent histogram bins containing at least 50% of the intensity countsresults in a window W which is 12 bins wide and includes the intensityvalues between 120 and

The average intensity for the static ROI is then computed using only thevalues inside the window determined above, i.e., the number of pixels ina bin multiplied with the intensity in that bin and summed over all binswithin the window W.

This approach excludes the intensity outliers (both low and highintensity values) from the computation of the average intensityrepresenting the myocardial blush value in the ROI. In other words, onlyintensity values between 120 and 131 within the ROI are included in thesubsequent calculation.

FIG. 4 shows the location of pixels within the static ROI with intensityvalues within the window W (according to the selection criterion thatabout 50% of the intensity values are located within the window W). Thebright areas indicate the pixels included. As can be seen, the area withthe included pixels need not be contiguous.

FIG. 5 shows the static ROI of FIG. 2 (top image) and a smaller staticROI (bottom image) located within the ROI of the top image. The smallerROI includes less arterial blood vessels.

FIG. 6 shows schematically the computed average intensity for both thestatic ROIs of FIG. 5 taken over a 28 second time interval. The elapsedtime (from the point an increase in the intensity was detected, inseconds) is plotted on the abscissa, and the average intensity for thestatic ROI (in arbitrary units) is plotted on the ordinate. The twocurves match within about 1-3 percent.

The maximum blush is approximately 112 [arb. units], the blush ratemeasured over about 6.1 sec from about zero blush to about the maximumvalue is in linear approximation about 16.2 [arb. units]/sec, and thewashout rate measured over about 6.1 sec from about the maximum blushvalue to about 15-20% blush is in linear approximation about 10.5 [arb.units]/sec. Blush appears to increase and decrease (washout)exponentially, so the linear curve fitting described above should beconsidered only as an approximation, Other characteristic values of thecurves of FIG. 6, such as a maximum slope or a curve fit with anexponential rise and decay time may also be used.

The average blush and the blush and washout rates obtained with thistechnique agree with the blush values perceived by the naked eye.

The static ROI algorithm described above does not rely on image trackingand is generally insensitive to the motion artifacts because of theexclusion of outliers. It is computationally fast and works well withboth low and high contrast images.

FIG. 7 shows pictures of the heart before and after a surgical procedurehas been performed on the heart. A comparison of the blush determinedwith the aforedescribed method of the invention before and after theprocedure can be used to determine whether perfusion has improved as aresult of the procedure.

For obtaining reliable and meaningful results, the ICG dosage,illumination level and camera sensitivity settings should be adjusted sothat the detector in the camera does not saturate when areas in theimage, such as arteries, reach their maximum intensity. If the cameranevertheless does saturate, the user needs to decide whether thecomputed blush rate and washout rate are likely to represent the actualrates, had the detector not saturated.

Two approaches are proposed for comparing image data obtained before andafter the procedure: (1) comparing the blush and washout rates beforeand after the procedure; and (2) comparing the elapsed time from bloodvessel peak intensity to maximum blush on images taken before and afterthe procedure.

With the first approach, a time series of fluorescence images of theanatomy is acquired before (top image of FIG. 7) and after the surgicalprocedure (bottom image of FIG. 7) by, for example, injecting a bolus ofICG dye. Only one of the time series of images is shown. A ROI isdelineated in each of the images in approximately the same area of theanatomy. The average intensity of the blush is then determined in eachof, or in a subset of, the fluorescence images in the time series withthe method of the invention described above with reference to thehistogram of FIG. 3, which excludes outliers, such as arteries. Theaverage ROI intensity from each image in the time series is normalizedto the baseline average intensity of the ROI in the first frame tocorrect for residual ICG that may have remained in the system.

FIG. 8 shows schematically the computed average intensities (about 50%of the intensity values are located within the window W of a histogramcorresponding to the histogram of FIG. 3) for the static ROIs of FIG. 7taken over a 28 second time interval. The top graph represents valuesbefore the procedure and the bottom graph values after the procedure.The elapsed time (from the point an increase in the intensity wasdetected, in seconds) is plotted on the abscissa, and the averageintensity for the static ROI (in arbitrary units) is plotted on theordinate. The broken line through the data represents a smoothed curveof the raw data. This helps to mask variation in the measurement due tomotion caused by the cardiac cycle or respiration and serves as a visualguide for assessing the blush rate and washout rate. As mentioned above,saturation of the sensor should be avoided, because saturation wouldmake an absolute determination of the slope impractical.

The blush and washout rates are determined from the corresponding slopesof straight lines connecting the 5% and 95% points in the averageintensity curves, i.e., the start of blush is taken as the time at whichthe intensity rises above the baseline by 5% of its maximum value, andthe 95% point is the time at which the intensity reaches 95% of itsmaximum value. The same applies to the determination of the washoutrate, with the 5% point at the end of washout determined with referenceto the final values, which may be higher than the initial 5% point dueto residual IeG remaining in the myocardial tissue. The 5% and 95%thresholds are heuristic thresholds used to discount for any noise thatmay appear in the image both before the blush appears, and as it nearsits maximum value.

It will be understood that the slope of the straight lines represents anaverage rate, and that the rate can also be determined from aleast-square curve fit or by selecting points other than 5% and 95%, asdescribed in the illustrated example.

As indicated in FIG. 8, the blush rate following the procedure is about43 units/sec, compared to about 18 units/sec before the procedure,representing an improvement of about 140%. Likewise, the washout ratefollowing the procedure is about 21 units/sec, compared to about 10units/sec before the procedure, representing an improvement of more than100%. Greater perfusion (blush) and washout rates suggest fastermovement of blood and greater maximum blush suggests a greater volume ofICG-bound blood in the tissue and are hence clear indicators of improvedperfusion through the tissue.

With the second approach, perfusion is determined from the time ofmaximum blood vessel (artery) intensity to maximum myocardial blush. Forexample, for cardiac surgery, the surgeon would draw two regions ofinterest (ROI), a first region covering the coronary artery feedingblood to the heart and a second region covering myocardial tissuereceiving blood from that artery. The maximum myocardial blush isdetermined from the histogram of the first region, as described above(FIG. 8). Peak intensity of the blood vessel may advantageously bedetermined from an area in the first region showing pixel intensitygreater than that of the surrounding tissue. For example, a histogram ofthe grayscale intensity values may be constructed for the first regionand a sliding window W applied across the abscissa, wherein the smallestset of adjacent histogram bins containing a predetermined percentage,for example about 20%, of the pixels with the highest intensity. Thelower percentage of pixels included in the computation of the averageblood vessel intensity than for myocardial tissue gives the user someflexibility in drawing a larger ROI over the vessel to make the resultless sensitive to lateral movement in the vessel during imageacquisition.

It will be understood that the first and second regions need not beseparate, but may 20 overlap or even be identical, as long as thefluorescence signals from the blood vessels and the myocardial tissuecan be clearly separated in the histogram.

It has been observed that before the procedure, the myocardial area mayreach maximum blush two seconds after the coronary artery reachesmaximum fluorescence intensity. After the procedure, it may only takeone second for the myocardial blush to reach maximum blush after thecoronary artery reaches maximum fluorescence intensity following thevessel reaching maximum. This finding would lead to the conclusion thatcardiac function has improved.

As mentioned above, a blood vessel may move laterally during imageacquisition which may make it more difficult to reliably determine thefluorescence intensity, for example during ICG imaging, of a coronaryartery. The proposed method provides a means for tracking the movementof the vessel by determining several, typically three, lines whichfollow the contour of a segment of interest of the blood vessel andapproximately span the width of the vessel.

According to the method, features or edges in the image are determinedby filtering using a convolution with the Laplacian-of-a-Gaussiankernel. The detected edges may be enhanced (thickened) by defining theedge by a width of at least two pixels. Both the original and theedge-enhanced images are stored.

Referring now to FIGS. 9 and 10, an operator delimits the segment of thevessel of interest by drawing two lines across the vessel, for examplewith a computer mouse (FIG. 9). The system then uses the previouslydetermined edge information to detect the segment of each line locatedbetween the vessel edges and the mid-point of that segment, which isnecessarily also the mid-point of the vessel, and constructs a linenormal to each line segment (FIG. 10). Thereafter, the system aligns twoline normals with the major longitudinal axis of the vessel (FIG. 11).

Next, the system constructs a series of 3 parallel lines, for examplecubic spline, of approximately equal length joining the two ends of thesegment of interest. However, a greater or lesser number of lines can beused. The lines have at their respective end points the same slope asthe respective line normals. Three exemplary lines which approximatelyspan the width of the vessel are shown in FIG. 12. The pixel intensityis sampled at points of each line along the longitudinal axis of thevessel. Preferably, intensities are averaged across the three lines ateach location along the longitudinal axis to produce an average vesselintensity at each location in the vessel. As indicated in the insert atthe top left corner of FIG. 12, the average intensity in the vesselsegment is approximately 55, substantially independent of thelongitudinal location in the vessel.

The process is then repeated for the time series of imagesframe-by-frame, while making sure that the positions match from oneframe to the next.

FIG. 13 illustrates a final frame in the image sequence processed inthis manner. The insert at the top left corner of FIG. 13 shows, as inFIG. 12, the averaged pixel intensity along the three lines. The segmentnow fluoresces noticeably stronger with an average intensity in thevessel segment of approximately 179. The insert at the top right cornerof FIG. 13 shows the change in the average intensity for all of theprocessed time-ordered frame sequence of images. The “fill time” of theblood vessel can be calculated from the slope of the latter curve (pixelintensity vs. time).

The preceding concepts can be extended to develop quantitative indicesuseful for intraoperative assessment of blood flow in surgical flaps andfor identifying vascular compromise.

Assuming that there is a peak having maximum fluorescence, the followingmetrics can be computed from the image sequence. If there is no peak,there is likely total arterial occlusion in the flap.

I′_(in) is a measure for the rate of change of increasing perfusion withtime as evidenced by the rate of ICG ingress or wash-in.

I′_(Out) is a measure for the rate of change of decreasing perfusionwith time after reaching maximum fluorescence intensity as evidenced bythe rate of ICG egress or wash-out.

Each of the measures may be taken on a flap either pre- andpost-operatively or, once the flap is in place, the measures may betaken from the flap and from adjacent native tissue.

With

I′_(in-Pre) being the rate of ICG ingress measured on either adjacentnative tissue or on the flap pre-operatively,

I′_(in-Post) being the rate of ICG ingress measured on the flappost-operatively, Similarly,

I′_(Out-Pre) being the rate of ICG egress measured on either adjacentnative tissue or on the flap pre-operatively, and

I′_(Out-Post) being the rate of ICG egress measured on the flappost-operatively,

the Wash-in Ratio WR_(In) can be defined as:

WR _(in) =I′ _(in-Post) /I′ _(in-Pre)

and the Wash-out Ratio WR_(Out) can be defined as:

WR _(out) =I′ _(Out-Post) /I′ _(Out-Pre).

WR_(In) and WR_(out) will be close to 1.0 in cases with normal vascularconditions.

WR_(In) will be significantly less than 1.0 in cases of arterial spasmor partial arterial occlusion. This metric will vary inversely to thedegree of arterial spasm or partial arterial occlusion; the amount bywhich this metric is less than 1.0 will correlate with increasedarterial spasm or arterial occlusion.

WR_(Out) will be significantly less than 1.0 in cases of venouscongestion. This metric will vary inversely to the degree of venouscongestion; the amount by which this metric is less than 1.0 willcorrelate with increased venous congestion.

While the invention is receptive to various modifications, andalternative forms, specific examples thereof have been shown in thedrawings and are herein described in detail. It should be understood,however, that the invention is not limited to the particular forms ormethods disclosed, but to the contrary, the invention is meant to coverall modifications, equivalents, and alternatives falling within thespirit and scope of the appended claims.

What is claimed is:
 1. A method for tracking a blood vessel in an image,comprising the steps of: (a) acquiring a fluorescence image of tissuecontaining a blood vessel; (b) delimiting a segment of the blood vesselwith boundaries oriented substantially perpendicular to a longitudinaldirection of the blood vessel; (c) constructing at least one curveextending between the delimiting boundaries and located within lateralvessel walls of the blood vessel, wherein the at least one curveterminates at the delimiting boundaries substantially perpendicular tothe boundaries; and (d) determining a fluorescence signal intensity inthe fluorescence image along the at least one curve, with the signalintensity being representative of vessel perfusion.
 2. The method ofclaim 1, wherein the at least one curve is defined by a spline function.3. The method of claim 1, wherein constructing at least one curveincludes constructing a plurality of curves and determining thefluorescence signal intensity includes averaging the signal intensityfrom points on the plurality of curves having a substantially identicaldistance from one of the delimiting boundaries.
 4. The method of claim1, wherein a position of the lateral vessel walls in the fluorescenceimage is detected by an edge-detection algorithm.
 5. The method of claim4, wherein the edge-detection algorithm is implemented with aLaplacian-of-a-Gaussian operator.
 6. The method of claim 4, furthercomprising the steps of: acquiring time-sequential fluorescence imagesof the tissue containing the blood vessel; determining characteristicdimensions of the delimited segment from the location of the lateralvessel walls in a first image; determining positions of lateral vesselwalls in at least one second image; matching the characteristicdimensions from the first image to the positions of lateral vessel wallsin the second image to find a location of the lateral vessel walls ofthe first image in the at least one second image; and repeating steps(c) and (d) for the at least one second image.
 7. The method of claim 6,further comprising: computing an average fluorescence signal intensityof all points along the curve, and determining a change in perfusion ofthe blood vessel from a change in the average fluorescence signalintensity between the time-sequential images.